Finding Frequent Itemsets

We assume there is a number $s$ , called the support threshold. If $I$ is a set of items (or an itemset), the support for $I$ is the number of baskets for which $I$ is a subset. We say $I$ is frequent if its support is $s$ or more. Given a universal set of items, a list of baskets (which are subsets of items), and a threshold $s$ , determine all frequent itemsets.

Parameters

$n$ : total number of transactions (size of database)

Filters

Computational Model

Randomization

Approximation

Algorithms Table

Displaying 4 of 4 algorithms


The Multistage Algorithm	1999	$O(n^2)$	$O(n^2)$
The Multihash Algorithm	1999	$O(n^2)$	$O(n^2)$
The Algorithm of Park; Chen; and Yu (PCY)	1995	$O(n^2)$	$O(n^2)$
A-Priori algorithm	1994	$O(n^2)$	$O(n^2)$

Reductions Table

Insuffient Data to display table

Other relevant algorithms